Successive Group Selection for Microaggregation

A method that solves the statistical disclosure control (Microaggregation)

This code is a simple(not speed optimized) implementation of GSMS_T2
based on the paper [1]. This implementaion does not use the speed
optimazations of [1]. You can use this software for non commercial purposes. Please, cite the article [1].
If you want to use the software for commercial purpose you have to contact with the authors of [1].
[1] C. Panagiotakis and G. Tziritas, Successive Group Selection for Microaggregation, IEEE Trans. on Knowledge and Data Engineering, vol.25, no.5, pp.1191-1195, May 2013.
In this work, we implement an efficient clustering algorithm that has been applied to the microaggregation problem. The goal is to partition N given records into clusters, each of them grouping at least K records, so that the sum of the within-partition squared error (SSE) is minimized. We propose a successive Group Selection algorithm that approximately solves the microaggregation problem based on sequential Minimization of SSE. Experimental results and comparisons to existing methods with similar computation cost on real and synthetic data sets demonstrate the high performance and robustness of the proposed scheme.
For more details visit: www.csd.uoc.gr/~cpanag
www.csd.uoc.gr/~tziritas